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Multifocal Image Fusion Based on NSCT


B. Anandhaprabakaran, S. Sabarish, P. Thiyagaraj, M. Thiyagarajan
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To overcome the difficulties of sub-band coefficients selection in multiscale transform domain-based image fusion and solve the problem of block effects suffered by spatial domain-based image fusion, this paper presents a novel hybrid multifocus image fusion method. First, the source multifocus images are decomposed using the non-subsampled contourlet transform (NSCT). The low-frequency sub-band coefficients are fused by the sum-modified-Laplacian-based local visual contrast, whereas the high-frequency sub-band coefficients are fused by the local Log-Gabor energy. The initial fused image is subsequently reconstructed based on the inverse NSCT with the fused coefficients. Second, after analyzing the similarity between the previous fused image and the source images, the initial focus area detection map is obtained, used for achieving the decision map obtained by employing a mathematical morphology post processing technique. Finally, based on the decision map, the final fused image is obtained by selecting the pixels in the focus areas and retaining the pixels in the focus region boundary as their corresponding pixels in the initial fused image. Experimental results demonstrate that the proposed method is better than various existing transform-based fusion methods, including gradient pyramid transform, discrete wavelet transform, NSCT, and a spatial-based method, in terms of both subjective and objective evaluations.

B. Anandhaprabakaran, S. Sabarish, P. Thiyagaraj, M. Thiyagarajan

Multi-focus image fusion, non-sub sampled contourlet transform, Log-Gabor energy, focused area detection, mathematical morphology.

  1. Y. Jiang and M. Wang, "Image fusion with morphological component analysis," Inf. Fusion, vol. 18, no. 1, pp. 107–118, Jul. 2014.
  2. S. Li and B. Yang, "Hybrid multiresolution method for multisensor multimodal image fusion," IEEE Sensors J., vol. 10, no. 9, pp. 1519–1526, Sep. 2010.
  3. S. Chen, R. Zhang, H. Su, J. Tian, and J. Xia, "SAR and multispectral image fusion using generalized IHS transform based on à trous wavelet and EMD decompositions," IEEE Sensors J., vol. 10, no. 3, pp. 737–745, Mar. 2010.
  4. J. Liang, Y. He, D. Liu, and X. Zeng, "Image fusion using higher order singular value decomposition," IEEE Trans. Image Process., vol. 21, no. 5, pp. 2898–2909, May 2012.
  5. B. Yang and S. Li, "Multi-focus image fusion using watershed transform and morphological wavelet clarity measure," Int. J. Innovative Comput. Inf. Control., vol. 7, no. 5A, pp. 2503–2514, May 2011.
  6. B. Yang and S. Li, "Multifocus image fusion and restoration with sparse representation," IEEE Trans. Instrum. Meas., vol. 59, no. 4, pp. 884–892, Apr. 2010.
  7. W. Wang and F. Chang, "A multi-focus image fusion method based on Laplacian pyramid," J. Comput., vol. 6, no. 12, pp. 2559–2566, Dec. 2011.
  8. N. Mitianoudis and T. Stathaki, "Optimal contrast correction for ICA-based fusion of multimodal images," IEEE Sensors J., vol. 8, no. 12, pp. 2016–2026, Dec. 2008.
  9. V. Aslantas and R. Kurban, "Fusion of multi-focus images using differential evolution algorithm," Expert Syst. Appl., vol. 37, no. 12, pp. 8861–8870, Dec. 2010.
  10. I. De and B. Chanda, "Multi-focus image fusion using a morphologybased focus measure in a quad-tree structure," Inf. Fusion, vol. 14, no. 2, pp. 136–146, Apr. 2013.
  11. S. Li, J. T. Kwok, and Y. Wang, "Multifocus image fusion using artificial neural networks," Pattern Recognit. Lett., vol. 23, no. 8, pp. 985–997, Jun. 2002.
  12. J. Tian, L. Chen, L. Ma, and W. Yu, "Multi-focus image fusion using a bilateral gradient-based sharpness criterion," Opt. Commun., vol. 284, no. 1, pp. 80–87, Jan. 2011.
  13. G. Piella, "A general framework for multiresolution image fusion: From pixels to regions," Inf. Fusion, vol. 4, no. 4, pp. 259–280, Dec. 2003.
  14. S. Li, X. Kang, J. Hu, and B. Yang, "Image matting for fusion of multi-focus images in dynamic scenes," Inf. Fusion, vol. 14, no. 2, pp. 147–162, Apr. 2013.
  15. Y. Liu, J. Jin, Q. Wang, Y. Shen, and X. Dong, "Region level based multi-focus image fusion using quaternion wavelet and normalized cut," Signal Process., vol. 97, pp. 9–30, Apr. 2014.
  16. B. Aiazzi, L. Alparone, A. Barducci, S. Baronti, and I. Pippi, "Multispectral fusion of multisensor image data by the generalized Laplacian pyramid," in Proc. IEEE Int. Geosci. Remote Sens. Symp., Hamburg, Germany, Jun. 1999, pp. 1183–1185.
  17. V. S. Petrovic and C. S. Xydeas, "Gradient-based multiresolution image fusion," IEEE Trans. Image Process., vol. 13, no. 2, pp. 228–237, Feb. 2004.
  18. Y. Yang, S. Y. Huang, J. Gao, and Z. Qian, "Multi-focus image fusion using an effective discrete wavelet transform based algorithm," Meas. Sci. Rev., vol. 14, no. 2, pp. 102–108, Apr. 2014.
  19. H. Li, B. S. Manjunath, and S. K. Mitra, "Multisensor image fusion using the wavelet transform," Graph. Models Image Process., vol. 57, no. 3, pp. 235–245, May 1995.

Publication Details

Published in : Volume 2 | Issue 2 | March-April - 2016
Date of Publication Print ISSN Online ISSN
2016-04-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
564-567 IJSRSET1622180   Technoscience Academy

Cite This Article

B. Anandhaprabakaran, S. Sabarish, P. Thiyagaraj, M. Thiyagarajan, "Multifocal Image Fusion Based on NSCT ", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 2, pp.564-567, March-April-2016.
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